Decoding ‘Agentic AI’ and Orchestration: Stacysherman Breaks Down CX Implications

In a recent LinkedIn post, Stacysherman delves into the often-confusing terms “agentic AI” and “orchestration,” aiming to clarify their practical implications for customer experience (CX). Stacysherman highlights that many professionals, despite hearing these buzzwords frequently, struggle to grasp their real-world application and impact on customers.

Stacysherman notes the common questions arising from executives across various industries: “what do these terms actually do in practice, and how do I use them to improve my customers’ experience?” This widespread uncertainty prompted a deeper exploration into how established technology leaders are implementing these concepts.

“If you have heard ‘agentic AI’ and ‘orchestration’ more times than you can count, nodded along in meetings, and wondered what either one actually means for your customers, you are not alone.”

Understanding Agentic AI in Practice

Stacysherman’s article focuses on insights gathered from IBM, a company with a long history in technological and business transformation. The discussion centers on IBM’s “Winning the Moment” report, which Stacysherman translates into actionable advice for improving customer interactions. The goal, as articulated by Stacysherman, is to demystify these advanced AI concepts for a broader business audience.

The Role of IBM and Expert Insights

To gain clarity, Stacysherman spoke with Pierre Charchaflian, Vice President at IBM. This conversation, featured in episode 215 of the Doing CX Right® podcast, aimed to bridge the gap between theoretical AI capabilities and tangible CX improvements. Stacysherman emphasizes that practical application and large-scale implementation by companies with proven track records offer the most valuable lessons.

“I know enough to have strong opinions. Yet, we all have so much to learn, and the best insights come from companies that consistently do the work at scale.”

Key Takeaways for CX Strategy

The discussion with IBM, as presented by Stacysherman, offers several critical insights for businesses looking to leverage AI effectively. One significant point is the identification of the primary barrier to AI implementation.

Technology Stack Limitations vs. Budget

Contrary to common assumptions, Stacysherman reveals that the main obstacle for businesses isn’t financial constraints or a lack of talent, but rather limitations within their existing technology stacks. This suggests that companies need to focus on integrating AI into their current infrastructure rather than solely relying on increased budgets or hiring more staff.

Anticipating Customer Needs with AI

Furthermore, Stacysherman highlights AI’s capability to proactively address customer issues. As detailed in the insights shared, AI can be used to:

• Detect frustration signals from customers in real-time.
• Respond to these signals before a customer decides to disengage or leave.

This proactive approach, Stacysherman explains, is crucial for enhancing customer loyalty and satisfaction. It shifts the focus from reactive problem-solving to anticipating and meeting customer needs before they escalate.

“In Doing CX Right®‬ podcast episode 215, you’ll learn: … How AI can detect frustration signals and respond before a customer decides to leave”

Measuring CX Success Beyond Traditional Metrics

Stacysherman also points to the limitations of traditional metrics like Net Promoter Score (NPS) and Customer Satisfaction (CSAT). The post suggests that a different metric might be more effective in truly capturing the quality of customer experience, especially when leveraging advanced AI capabilities. This implies a need for businesses to re-evaluate how they measure CX success in the age of AI.

“What metric to use, and what NPS and CSAT overlook”

Ultimately, Stacysherman encourages businesses to consider whether their current CX strategies are designed to anticipate customer needs or if they still rely on customers to report problems. The insights shared aim to equip leaders with a clearer understanding of agentic AI and orchestration, enabling them to build more responsive and effective customer experiences.